#include "utility.h"
#include "lio_sam_6axis/cloud_info.h"
#include "lio_sam_6axis/save_map.h"

#include <gtsam/geometry/Rot3.h>
#include <gtsam/geometry/Pose3.h>
#include <gtsam/slam/PriorFactor.h>
#include <gtsam/slam/BetweenFactor.h>
#include <gtsam/navigation/GPSFactor.h>
#include <gtsam/navigation/ImuFactor.h>
#include <gtsam/navigation/CombinedImuFactor.h>
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
#include <gtsam/nonlinear/Marginals.h>
#include <gtsam/nonlinear/Values.h>
#include <gtsam/inference/Symbol.h>

#include <gtsam/nonlinear/ISAM2.h>

using namespace gtsam;

using symbol_shorthand::X; // Pose3 (x,y,z,r,p,y)
using symbol_shorthand::V; // Vel   (xdot,ydot,zdot)
using symbol_shorthand::B; // Bias  (ax,ay,az,gx,gy,gz)
using symbol_shorthand::G; // GPS pose

/*
    * A point cloud type that has 6D pose info ([x,y,z,roll,pitch,yaw] intensity is time stamp)
    */
struct PointXYZIRPYT
{
  PCL_ADD_POINT4D
      PCL_ADD_INTENSITY;                  // preferred way of adding a XYZ+padding
  float roll;
  float pitch;
  float yaw;
  double time;
  EIGEN_MAKE_ALIGNED_OPERATOR_NEW   // make sure our new allocators are aligned
} EIGEN_ALIGN16;                    // enforce SSE padding for correct memory alignment

POINT_CLOUD_REGISTER_POINT_STRUCT (PointXYZIRPYT,
(float, x, x) (float, y, y)
(float, z, z) (float, intensity, intensity)
(float, roll, roll) (float, pitch, pitch) (float, yaw, yaw)
(double, time, time))

typedef PointXYZIRPYT  PointTypePose;


class mapOptimization : public ParamServer
{

 public:

  // gtsam
  NonlinearFactorGraph gtSAMgraph;
  Values initialEstimate;
  Values optimizedEstimate;
  ISAM2 *isam;
  Values isamCurrentEstimate;
  Eigen::MatrixXd poseCovariance;

  ros::Publisher pubLaserCloudSurround;
  ros::Publisher pubLaserOdometryGlobal;
  ros::Publisher pubLaserOdometryIncremental;
  ros::Publisher pubKeyPoses;
  ros::Publisher pubPath;

  ros::Publisher pubHistoryKeyFrames;
  ros::Publisher pubIcpKeyFrames;
  ros::Publisher pubRecentKeyFrames;
  ros::Publisher pubRecentKeyFrame;
  ros::Publisher pubCloudRegisteredRaw;
  ros::Publisher pubLoopConstraintEdge;

  ros::Publisher pubSLAMInfo;

  ros::Subscriber subCloud;
  ros::Subscriber subGPS;
  ros::Subscriber subLoop;

  ros::ServiceServer srvSaveMap;

  std::deque<nav_msgs::Odometry> gpsQueue;
  lio_sam_6axis::cloud_info cloudInfo;

  vector<pcl::PointCloud<PointType>::Ptr> cornerCloudKeyFrames;
  vector<pcl::PointCloud<PointType>::Ptr> surfCloudKeyFrames;

  pcl::PointCloud<PointType>::Ptr cloudKeyPoses3D;
  pcl::PointCloud<PointTypePose>::Ptr cloudKeyPoses6D;
  pcl::PointCloud<PointType>::Ptr copy_cloudKeyPoses3D;
  pcl::PointCloud<PointTypePose>::Ptr copy_cloudKeyPoses6D;

  pcl::PointCloud<PointType>::Ptr laserCloudCornerLast; // corner feature set from odoOptimization
  pcl::PointCloud<PointType>::Ptr laserCloudSurfLast; // surf feature set from odoOptimization
  pcl::PointCloud<PointType>::Ptr laserCloudCornerLastDS; // downsampled corner feature set from odoOptimization
  pcl::PointCloud<PointType>::Ptr laserCloudSurfLastDS; // downsampled surf feature set from odoOptimization

  pcl::PointCloud<PointType>::Ptr laserCloudOri;
  pcl::PointCloud<PointType>::Ptr coeffSel;

  std::vector<PointType> laserCloudOriCornerVec; // corner point holder for parallel computation
  std::vector<PointType> coeffSelCornerVec;
  std::vector<bool> laserCloudOriCornerFlag;
  std::vector<PointType> laserCloudOriSurfVec; // surf point holder for parallel computation
  std::vector<PointType> coeffSelSurfVec;
  std::vector<bool> laserCloudOriSurfFlag;

  map<int, pair<pcl::PointCloud<PointType>, pcl::PointCloud<PointType>>> laserCloudMapContainer;
  pcl::PointCloud<PointType>::Ptr laserCloudCornerFromMap;
  pcl::PointCloud<PointType>::Ptr laserCloudSurfFromMap;
  pcl::PointCloud<PointType>::Ptr laserCloudCornerFromMapDS;
  pcl::PointCloud<PointType>::Ptr laserCloudSurfFromMapDS;

  pcl::KdTreeFLANN<PointType>::Ptr kdtreeCornerFromMap;
  pcl::KdTreeFLANN<PointType>::Ptr kdtreeSurfFromMap;

  pcl::KdTreeFLANN<PointType>::Ptr kdtreeSurroundingKeyPoses;
  pcl::KdTreeFLANN<PointType>::Ptr kdtreeHistoryKeyPoses;

  pcl::VoxelGrid<PointType> downSizeFilterCorner;
  pcl::VoxelGrid<PointType> downSizeFilterSurf;
  pcl::VoxelGrid<PointType> downSizeFilterICP;
  pcl::VoxelGrid<PointType> downSizeFilterSurroundingKeyPoses; // for surrounding key poses of scan-to-map optimization

  ros::Time timeLaserInfoStamp;
  double timeLaserInfoCur;

  float transformTobeMapped[6];

  std::mutex mtx;
  std::mutex mtxLoopInfo;

  bool isDegenerate = false;
  cv::Mat matP;

  int laserCloudCornerFromMapDSNum = 0;
  int laserCloudSurfFromMapDSNum = 0;
  int laserCloudCornerLastDSNum = 0;
  int laserCloudSurfLastDSNum = 0;

  bool aLoopIsClosed = false;
  map<int, int> loopIndexContainer; // from new to old
  vector<pair<int, int>> loopIndexQueue;
  vector<gtsam::Pose3> loopPoseQueue;
  vector<gtsam::noiseModel::Diagonal::shared_ptr> loopNoiseQueue;
  deque<std_msgs::Float64MultiArray> loopInfoVec;

  nav_msgs::Path globalPath;

  Eigen::Affine3f transPointAssociateToMap;
  Eigen::Affine3f incrementalOdometryAffineFront;
  Eigen::Affine3f incrementalOdometryAffineBack;


  mapOptimization()
  {
    ISAM2Params parameters;
    parameters.relinearizeThreshold = 0.1;
    parameters.relinearizeSkip = 1;
    isam = new ISAM2(parameters);

    pubKeyPoses                 = nh.advertise<sensor_msgs::PointCloud2>("lio_sam_6axis/mapping/trajectory", 1);
    pubLaserCloudSurround       = nh.advertise<sensor_msgs::PointCloud2>("lio_sam_6axis/mapping/map_global", 1);
    pubLaserOdometryGlobal      = nh.advertise<nav_msgs::Odometry> ("lio_sam_6axis/mapping/odometry", 1);
    pubLaserOdometryIncremental = nh.advertise<nav_msgs::Odometry> ("lio_sam_6axis/mapping/odometry_incremental", 1);
    pubPath                     = nh.advertise<nav_msgs::Path>("path", 1);

    subCloud = nh.subscribe<lio_sam_6axis::cloud_info>("lio_sam_6axis/feature/cloud_info", 1, &mapOptimization::laserCloudInfoHandler, this, ros::TransportHints().tcpNoDelay());
    subGPS   = nh.subscribe<nav_msgs::Odometry> (gpsTopic, 200, &mapOptimization::gpsHandler, this, ros::TransportHints().tcpNoDelay());
    subLoop  = nh.subscribe<std_msgs::Float64MultiArray>("lio_loop/loop_closure_detection", 1, &mapOptimization::loopInfoHandler, this, ros::TransportHints().tcpNoDelay());

    srvSaveMap  = nh.advertiseService("lio_sam_6axis/save_map", &mapOptimization::saveMapService, this);

    pubHistoryKeyFrames   = nh.advertise<sensor_msgs::PointCloud2>("lio_sam_6axis/mapping/icp_loop_closure_history_cloud", 1);
    pubIcpKeyFrames       = nh.advertise<sensor_msgs::PointCloud2>("lio_sam_6axis/mapping/icp_loop_closure_corrected_cloud", 1);
    pubLoopConstraintEdge = nh.advertise<visualization_msgs::MarkerArray>("/lio_sam_6axis/mapping/loop_closure_constraints", 1);

    pubRecentKeyFrames    = nh.advertise<sensor_msgs::PointCloud2>("lio_sam_6axis/mapping/map_local", 1);
    pubRecentKeyFrame     = nh.advertise<sensor_msgs::PointCloud2>("lio_sam_6axis/mapping/cloud_registered", 1);
    pubCloudRegisteredRaw = nh.advertise<sensor_msgs::PointCloud2>("lio_sam_6axis/mapping/cloud_registered_raw", 1);
//    pubCloudRegisteredRaw = nh.advertise<sensor_msgs::PointCloud2>("lio_sam_6axis/mapping/cloud_registered_raw", 1);

    pubSLAMInfo           = nh.advertise<lio_sam_6axis::cloud_info>("lio_sam_6axis/mapping/slam_info", 1);

    downSizeFilterCorner.setLeafSize(mappingCornerLeafSize, mappingCornerLeafSize, mappingCornerLeafSize);
    downSizeFilterSurf.setLeafSize(mappingSurfLeafSize, mappingSurfLeafSize, mappingSurfLeafSize);
    downSizeFilterICP.setLeafSize(mappingSurfLeafSize, mappingSurfLeafSize, mappingSurfLeafSize);
    downSizeFilterSurroundingKeyPoses.setLeafSize(surroundingKeyframeDensity, surroundingKeyframeDensity, surroundingKeyframeDensity); // for surrounding key poses of scan-to-map optimization

    allocateMemory();
  }

  void allocateMemory()
  {
    cloudKeyPoses3D.reset(new pcl::PointCloud<PointType>());
    cloudKeyPoses6D.reset(new pcl::PointCloud<PointTypePose>());
    copy_cloudKeyPoses3D.reset(new pcl::PointCloud<PointType>());
    copy_cloudKeyPoses6D.reset(new pcl::PointCloud<PointTypePose>());

    kdtreeSurroundingKeyPoses.reset(new pcl::KdTreeFLANN<PointType>());
    kdtreeHistoryKeyPoses.reset(new pcl::KdTreeFLANN<PointType>());

    laserCloudCornerLast.reset(new pcl::PointCloud<PointType>()); // corner feature set from odoOptimization
    laserCloudSurfLast.reset(new pcl::PointCloud<PointType>()); // surf feature set from odoOptimization
    laserCloudCornerLastDS.reset(new pcl::PointCloud<PointType>()); // downsampled corner featuer set from odoOptimization
    laserCloudSurfLastDS.reset(new pcl::PointCloud<PointType>()); // downsampled surf featuer set from odoOptimization

    laserCloudOri.reset(new pcl::PointCloud<PointType>());
    coeffSel.reset(new pcl::PointCloud<PointType>());

    laserCloudOriCornerVec.resize(N_SCAN * Horizon_SCAN);
    coeffSelCornerVec.resize(N_SCAN * Horizon_SCAN);
    laserCloudOriCornerFlag.resize(N_SCAN * Horizon_SCAN);
    laserCloudOriSurfVec.resize(N_SCAN * Horizon_SCAN);
    coeffSelSurfVec.resize(N_SCAN * Horizon_SCAN);
    laserCloudOriSurfFlag.resize(N_SCAN * Horizon_SCAN);

    std::fill(laserCloudOriCornerFlag.begin(), laserCloudOriCornerFlag.end(), false);
    std::fill(laserCloudOriSurfFlag.begin(), laserCloudOriSurfFlag.end(), false);

    laserCloudCornerFromMap.reset(new pcl::PointCloud<PointType>());
    laserCloudSurfFromMap.reset(new pcl::PointCloud<PointType>());
    laserCloudCornerFromMapDS.reset(new pcl::PointCloud<PointType>());
    laserCloudSurfFromMapDS.reset(new pcl::PointCloud<PointType>());

    kdtreeCornerFromMap.reset(new pcl::KdTreeFLANN<PointType>());
    kdtreeSurfFromMap.reset(new pcl::KdTreeFLANN<PointType>());

    for (int i = 0; i < 6; ++i){
      transformTobeMapped[i] = 0;
    }

    matP = cv::Mat(6, 6, CV_32F, cv::Scalar::all(0));
  }

  void laserCloudInfoHandler(const lio_sam_6axis::cloud_infoConstPtr& msgIn)
  {
    // extract time stamp
    timeLaserInfoStamp = msgIn->header.stamp;
    timeLaserInfoCur = msgIn->header.stamp.toSec();

    // extract info and feature cloud
    cloudInfo = *msgIn;
    pcl::fromROSMsg(msgIn->cloud_corner,  *laserCloudCornerLast);
    pcl::fromROSMsg(msgIn->cloud_surface, *laserCloudSurfLast);

    std::lock_guard<std::mutex> lock(mtx);

    static double timeLastProcessing = -1;
    if (timeLaserInfoCur - timeLastProcessing >= mappingProcessInterval)
    {
      timeLastProcessing = timeLaserInfoCur;

      updateInitialGuess();

      extractSurroundingKeyFrames();

      downsampleCurrentScan();

      scan2MapOptimization();

      saveKeyFramesAndFactor();

      correctPoses();

      publishOdometry();

      publishFrames();
    }
  }

  void gpsHandler(const nav_msgs::Odometry::ConstPtr& gpsMsg)
  {
    gpsQueue.push_back(*gpsMsg);
  }

  void pointAssociateToMap(PointType const * const pi, PointType * const po)
  {
    po->x = transPointAssociateToMap(0,0) * pi->x + transPointAssociateToMap(0,1) * pi->y + transPointAssociateToMap(0,2) * pi->z + transPointAssociateToMap(0,3);
    po->y = transPointAssociateToMap(1,0) * pi->x + transPointAssociateToMap(1,1) * pi->y + transPointAssociateToMap(1,2) * pi->z + transPointAssociateToMap(1,3);
    po->z = transPointAssociateToMap(2,0) * pi->x + transPointAssociateToMap(2,1) * pi->y + transPointAssociateToMap(2,2) * pi->z + transPointAssociateToMap(2,3);
    po->intensity = pi->intensity;
  }

  pcl::PointCloud<PointType>::Ptr transformPointCloud(pcl::PointCloud<PointType>::Ptr cloudIn, PointTypePose* transformIn)
  {
    pcl::PointCloud<PointType>::Ptr cloudOut(new pcl::PointCloud<PointType>());

    int cloudSize = cloudIn->size();
    cloudOut->resize(cloudSize);

    Eigen::Affine3f transCur = pcl::getTransformation(transformIn->x, transformIn->y, transformIn->z, transformIn->roll, transformIn->pitch, transformIn->yaw);

#pragma omp parallel for num_threads(numberOfCores)
    for (int i = 0; i < cloudSize; ++i)
    {
      const auto &pointFrom = cloudIn->points[i];
      cloudOut->points[i].x = transCur(0,0) * pointFrom.x + transCur(0,1) * pointFrom.y + transCur(0,2) * pointFrom.z + transCur(0,3);
      cloudOut->points[i].y = transCur(1,0) * pointFrom.x + transCur(1,1) * pointFrom.y + transCur(1,2) * pointFrom.z + transCur(1,3);
      cloudOut->points[i].z = transCur(2,0) * pointFrom.x + transCur(2,1) * pointFrom.y + transCur(2,2) * pointFrom.z + transCur(2,3);
      cloudOut->points[i].intensity = pointFrom.intensity;
    }
    return cloudOut;
  }

  gtsam::Pose3 pclPointTogtsamPose3(PointTypePose thisPoint)
  {
    return gtsam::Pose3(gtsam::Rot3::RzRyRx(double(thisPoint.roll), double(thisPoint.pitch), double(thisPoint.yaw)),
                        gtsam::Point3(double(thisPoint.x),    double(thisPoint.y),     double(thisPoint.z)));
  }

  gtsam::Pose3 trans2gtsamPose(float transformIn[])
  {
    return gtsam::Pose3(gtsam::Rot3::RzRyRx(transformIn[0], transformIn[1], transformIn[2]),
                        gtsam::Point3(transformIn[3], transformIn[4], transformIn[5]));
  }

  Eigen::Affine3f pclPointToAffine3f(PointTypePose thisPoint)
  {
    return pcl::getTransformation(thisPoint.x, thisPoint.y, thisPoint.z, thisPoint.roll, thisPoint.pitch, thisPoint.yaw);
  }

  Eigen::Affine3f trans2Affine3f(float transformIn[])
  {
    return pcl::getTransformation(transformIn[3], transformIn[4], transformIn[5], transformIn[0], transformIn[1], transformIn[2]);
  }

  PointTypePose trans2PointTypePose(float transformIn[])
  {
    PointTypePose thisPose6D;
    thisPose6D.x = transformIn[3];
    thisPose6D.y = transformIn[4];
    thisPose6D.z = transformIn[5];
    thisPose6D.roll  = transformIn[0];
    thisPose6D.pitch = transformIn[1];
    thisPose6D.yaw   = transformIn[2];
    return thisPose6D;
  }















  bool saveMapService(lio_sam_6axis::save_mapRequest& req, lio_sam_6axis::save_mapResponse& res)
  {
    string saveMapDirectory;

    cout << "****************************************************" << endl;
    cout << "Saving map to pcd files ..." << endl;
    if(req.destination.empty()) saveMapDirectory = std::getenv("HOME") + savePCDDirectory;
    else saveMapDirectory = std::getenv("HOME") + req.destination;
    cout << "Save destination: " << saveMapDirectory << endl;
    // create directory and remove old files;
    int unused = system((std::string("exec rm -r ") + saveMapDirectory).c_str());
    unused = system((std::string("mkdir -p ") + saveMapDirectory).c_str());
    // save key frame transformations
    pcl::io::savePCDFileBinary(saveMapDirectory + "/trajectory.pcd", *cloudKeyPoses3D);
    pcl::io::savePCDFileBinary(saveMapDirectory + "/transformations.pcd", *cloudKeyPoses6D);
    // extract global point cloud map
    pcl::PointCloud<PointType>::Ptr globalCornerCloud(new pcl::PointCloud<PointType>());
    pcl::PointCloud<PointType>::Ptr globalCornerCloudDS(new pcl::PointCloud<PointType>());
    pcl::PointCloud<PointType>::Ptr globalSurfCloud(new pcl::PointCloud<PointType>());
    pcl::PointCloud<PointType>::Ptr globalSurfCloudDS(new pcl::PointCloud<PointType>());
    pcl::PointCloud<PointType>::Ptr globalMapCloud(new pcl::PointCloud<PointType>());
    for (int i = 0; i < (int)cloudKeyPoses3D->size(); i++) {
      *globalCornerCloud += *transformPointCloud(cornerCloudKeyFrames[i],  &cloudKeyPoses6D->points[i]);
      *globalSurfCloud   += *transformPointCloud(surfCloudKeyFrames[i],    &cloudKeyPoses6D->points[i]);
      cout << "\r" << std::flush << "Processing feature cloud " << i << " of " << cloudKeyPoses6D->size() << " ...";
    }

    if(req.resolution != 0)
    {
      cout << "\n\nSave resolution: " << req.resolution << endl;

      // down-sample and save corner cloud
      downSizeFilterCorner.setInputCloud(globalCornerCloud);
      downSizeFilterCorner.setLeafSize(req.resolution, req.resolution, req.resolution);
      downSizeFilterCorner.filter(*globalCornerCloudDS);
      pcl::io::savePCDFileBinary(saveMapDirectory + "/CornerMap.pcd", *globalCornerCloudDS);
      // down-sample and save surf cloud
      downSizeFilterSurf.setInputCloud(globalSurfCloud);
      downSizeFilterSurf.setLeafSize(req.resolution, req.resolution, req.resolution);
      downSizeFilterSurf.filter(*globalSurfCloudDS);
      pcl::io::savePCDFileBinary(saveMapDirectory + "/SurfMap.pcd", *globalSurfCloudDS);
    }
    else
    {
      // save corner cloud
      pcl::io::savePCDFileBinary(saveMapDirectory + "/CornerMap.pcd", *globalCornerCloud);
      // save surf cloud
      pcl::io::savePCDFileBinary(saveMapDirectory + "/SurfMap.pcd", *globalSurfCloud);
    }

    // save global point cloud map
    *globalMapCloud += *globalCornerCloud;
    *globalMapCloud += *globalSurfCloud;

    int ret = pcl::io::savePCDFileBinary(saveMapDirectory + "/GlobalMap.pcd", *globalMapCloud);
    res.success = ret == 0;

    downSizeFilterCorner.setLeafSize(mappingCornerLeafSize, mappingCornerLeafSize, mappingCornerLeafSize);
    downSizeFilterSurf.setLeafSize(mappingSurfLeafSize, mappingSurfLeafSize, mappingSurfLeafSize);

    cout << "****************************************************" << endl;
    cout << "Saving map to pcd files completed\n" << endl;

    return true;
  }

  void visualizeGlobalMapThread()
  {
    ros::Rate rate(0.2);
    while (ros::ok()){
      rate.sleep();
      publishGlobalMap();
    }

    if (savePCD == false)
      return;

    lio_sam_6axis::save_mapRequest  req;
    lio_sam_6axis::save_mapResponse res;

    if(!saveMapService(req, res)){
      cout << "Fail to save map" << endl;
    }
  }

  void publishGlobalMap()
  {
    if (pubLaserCloudSurround.getNumSubscribers() == 0)
      return;

    if (cloudKeyPoses3D->points.empty() == true)
      return;

    pcl::KdTreeFLANN<PointType>::Ptr kdtreeGlobalMap(new pcl::KdTreeFLANN<PointType>());;
    pcl::PointCloud<PointType>::Ptr globalMapKeyPoses(new pcl::PointCloud<PointType>());
    pcl::PointCloud<PointType>::Ptr globalMapKeyPosesDS(new pcl::PointCloud<PointType>());
    pcl::PointCloud<PointType>::Ptr globalMapKeyFrames(new pcl::PointCloud<PointType>());
    pcl::PointCloud<PointType>::Ptr globalMapKeyFramesDS(new pcl::PointCloud<PointType>());

    // kd-tree to find near key frames to visualize
    std::vector<int> pointSearchIndGlobalMap;
    std::vector<float> pointSearchSqDisGlobalMap;
    // search near key frames to visualize
    mtx.lock();
    kdtreeGlobalMap->setInputCloud(cloudKeyPoses3D);
    kdtreeGlobalMap->radiusSearch(cloudKeyPoses3D->back(), globalMapVisualizationSearchRadius, pointSearchIndGlobalMap, pointSearchSqDisGlobalMap, 0);
    mtx.unlock();

    for (int i = 0; i < (int)pointSearchIndGlobalMap.size(); ++i)
      globalMapKeyPoses->push_back(cloudKeyPoses3D->points[pointSearchIndGlobalMap[i]]);
    // downsample near selected key frames
    pcl::VoxelGrid<PointType> downSizeFilterGlobalMapKeyPoses; // for global map visualization
    downSizeFilterGlobalMapKeyPoses.setLeafSize(globalMapVisualizationPoseDensity, globalMapVisualizationPoseDensity, globalMapVisualizationPoseDensity); // for global map visualization
    downSizeFilterGlobalMapKeyPoses.setInputCloud(globalMapKeyPoses);
    downSizeFilterGlobalMapKeyPoses.filter(*globalMapKeyPosesDS);
    for(auto& pt : globalMapKeyPosesDS->points)
    {
      kdtreeGlobalMap->nearestKSearch(pt, 1, pointSearchIndGlobalMap, pointSearchSqDisGlobalMap);
      pt.intensity = cloudKeyPoses3D->points[pointSearchIndGlobalMap[0]].intensity;
    }

    // extract visualized and downsampled key frames
    for (int i = 0; i < (int)globalMapKeyPosesDS->size(); ++i){
      if (pointDistance(globalMapKeyPosesDS->points[i], cloudKeyPoses3D->back()) > globalMapVisualizationSearchRadius)
        continue;
      int thisKeyInd = (int)globalMapKeyPosesDS->points[i].intensity;
      *globalMapKeyFrames += *transformPointCloud(cornerCloudKeyFrames[thisKeyInd],  &cloudKeyPoses6D->points[thisKeyInd]);
      *globalMapKeyFrames += *transformPointCloud(surfCloudKeyFrames[thisKeyInd],    &cloudKeyPoses6D->points[thisKeyInd]);
    }
    // downsample visualized points
    pcl::VoxelGrid<PointType> downSizeFilterGlobalMapKeyFrames; // for global map visualization
    downSizeFilterGlobalMapKeyFrames.setLeafSize(globalMapVisualizationLeafSize, globalMapVisualizationLeafSize, globalMapVisualizationLeafSize); // for global map visualization
    downSizeFilterGlobalMapKeyFrames.setInputCloud(globalMapKeyFrames);
    downSizeFilterGlobalMapKeyFrames.filter(*globalMapKeyFramesDS);
    publishCloud(pubLaserCloudSurround, globalMapKeyFramesDS, timeLaserInfoStamp, odometryFrame);
  }












  void loopClosureThread()
  {
    if (loopClosureEnableFlag == false)
      return;

    ros::Rate rate(loopClosureFrequency);
    while (ros::ok())
    {
      rate.sleep();
      performLoopClosure();
      visualizeLoopClosure();
    }
  }

  void loopInfoHandler(const std_msgs::Float64MultiArray::ConstPtr& loopMsg)
  {
    std::lock_guard<std::mutex> lock(mtxLoopInfo);
    if (loopMsg->data.size() != 2)
      return;

    loopInfoVec.push_back(*loopMsg);

    while (loopInfoVec.size() > 5)
      loopInfoVec.pop_front();
  }

  void performLoopClosure()
  {
    if (cloudKeyPoses3D->points.empty() == true)
      return;

    mtx.lock();
    *copy_cloudKeyPoses3D = *cloudKeyPoses3D;
    *copy_cloudKeyPoses6D = *cloudKeyPoses6D;
    mtx.unlock();

    // find keys
    int loopKeyCur;
    int loopKeyPre;
    if (detectLoopClosureExternal(&loopKeyCur, &loopKeyPre) == false)
      if (detectLoopClosureDistance(&loopKeyCur, &loopKeyPre) == false)
        return;

    // extract cloud
    pcl::PointCloud<PointType>::Ptr cureKeyframeCloud(new pcl::PointCloud<PointType>());
    pcl::PointCloud<PointType>::Ptr prevKeyframeCloud(new pcl::PointCloud<PointType>());
    {
      loopFindNearKeyframes(cureKeyframeCloud, loopKeyCur, 0);
      loopFindNearKeyframes(prevKeyframeCloud, loopKeyPre, historyKeyframeSearchNum);
      if (cureKeyframeCloud->size() < 300 || prevKeyframeCloud->size() < 1000)
        return;
      if (pubHistoryKeyFrames.getNumSubscribers() != 0)
        publishCloud(pubHistoryKeyFrames, prevKeyframeCloud, timeLaserInfoStamp, odometryFrame);
    }

    // ICP Settings
    static pcl::IterativeClosestPoint<PointType, PointType> icp;
    icp.setMaxCorrespondenceDistance(historyKeyframeSearchRadius*2);
    icp.setMaximumIterations(100);
    icp.setTransformationEpsilon(1e-6);
    icp.setEuclideanFitnessEpsilon(1e-6);
    icp.setRANSACIterations(0);

    // Align clouds
    icp.setInputSource(cureKeyframeCloud);
    icp.setInputTarget(prevKeyframeCloud);
    pcl::PointCloud<PointType>::Ptr unused_result(new pcl::PointCloud<PointType>());
    icp.align(*unused_result);

    if (icp.hasConverged() == false || icp.getFitnessScore() > historyKeyframeFitnessScore)
      return;

    // publish corrected cloud
    if (pubIcpKeyFrames.getNumSubscribers() != 0)
    {
      pcl::PointCloud<PointType>::Ptr closed_cloud(new pcl::PointCloud<PointType>());
      pcl::transformPointCloud(*cureKeyframeCloud, *closed_cloud, icp.getFinalTransformation());
      publishCloud(pubIcpKeyFrames, closed_cloud, timeLaserInfoStamp, odometryFrame);
    }

    // Get pose transformation
    float x, y, z, roll, pitch, yaw;
    Eigen::Affine3f correctionLidarFrame;
    correctionLidarFrame = icp.getFinalTransformation();
    // transform from world origin to wrong pose
    Eigen::Affine3f tWrong = pclPointToAffine3f(copy_cloudKeyPoses6D->points[loopKeyCur]);
    // transform from world origin to corrected pose
    Eigen::Affine3f tCorrect = correctionLidarFrame * tWrong;// pre-multiplying -> successive rotation about a fixed frame
    pcl::getTranslationAndEulerAngles (tCorrect, x, y, z, roll, pitch, yaw);
    gtsam::Pose3 poseFrom = Pose3(Rot3::RzRyRx(roll, pitch, yaw), Point3(x, y, z));
    gtsam::Pose3 poseTo = pclPointTogtsamPose3(copy_cloudKeyPoses6D->points[loopKeyPre]);
    gtsam::Vector Vector6(6);
    float noiseScore = icp.getFitnessScore();
    Vector6 << noiseScore, noiseScore, noiseScore, noiseScore, noiseScore, noiseScore;
    noiseModel::Diagonal::shared_ptr constraintNoise = noiseModel::Diagonal::Variances(Vector6);

    // Add pose constraint
    mtx.lock();
    loopIndexQueue.push_back(make_pair(loopKeyCur, loopKeyPre));
    loopPoseQueue.push_back(poseFrom.between(poseTo));
    loopNoiseQueue.push_back(constraintNoise);
    mtx.unlock();

    // add loop constriant
    loopIndexContainer[loopKeyCur] = loopKeyPre;
  }

  bool detectLoopClosureDistance(int *latestID, int *closestID)
  {
    int loopKeyCur = copy_cloudKeyPoses3D->size() - 1;
    int loopKeyPre = -1;

    // check loop constraint added before
    auto it = loopIndexContainer.find(loopKeyCur);
    if (it != loopIndexContainer.end())
      return false;

    // find the closest history key frame
    std::vector<int> pointSearchIndLoop;
    std::vector<float> pointSearchSqDisLoop;
    kdtreeHistoryKeyPoses->setInputCloud(copy_cloudKeyPoses3D);
    kdtreeHistoryKeyPoses->radiusSearch(copy_cloudKeyPoses3D->back(), historyKeyframeSearchRadius, pointSearchIndLoop, pointSearchSqDisLoop, 0);

    for (int i = 0; i < (int)pointSearchIndLoop.size(); ++i)
    {
      int id = pointSearchIndLoop[i];
      if (abs(copy_cloudKeyPoses6D->points[id].time - timeLaserInfoCur) > historyKeyframeSearchTimeDiff)
      {
        loopKeyPre = id;
        break;
      }
    }

    if (loopKeyPre == -1 || loopKeyCur == loopKeyPre)
      return false;

    *latestID = loopKeyCur;
    *closestID = loopKeyPre;

    return true;
  }

  bool detectLoopClosureExternal(int *latestID, int *closestID)
  {
    // this function is not used yet, please ignore it
    int loopKeyCur = -1;
    int loopKeyPre = -1;

    std::lock_guard<std::mutex> lock(mtxLoopInfo);
    if (loopInfoVec.empty())
      return false;

    double loopTimeCur = loopInfoVec.front().data[0];
    double loopTimePre = loopInfoVec.front().data[1];
    loopInfoVec.pop_front();

    if (abs(loopTimeCur - loopTimePre) < historyKeyframeSearchTimeDiff)
      return false;

    int cloudSize = copy_cloudKeyPoses6D->size();
    if (cloudSize < 2)
      return false;

    // latest key
    loopKeyCur = cloudSize - 1;
    for (int i = cloudSize - 1; i >= 0; --i)
    {
      if (copy_cloudKeyPoses6D->points[i].time >= loopTimeCur)
        loopKeyCur = round(copy_cloudKeyPoses6D->points[i].intensity);
      else
        break;
    }

    // previous key
    loopKeyPre = 0;
    for (int i = 0; i < cloudSize; ++i)
    {
      if (copy_cloudKeyPoses6D->points[i].time <= loopTimePre)
        loopKeyPre = round(copy_cloudKeyPoses6D->points[i].intensity);
      else
        break;
    }

    if (loopKeyCur == loopKeyPre)
      return false;

    auto it = loopIndexContainer.find(loopKeyCur);
    if (it != loopIndexContainer.end())
      return false;

    *latestID = loopKeyCur;
    *closestID = loopKeyPre;

    return true;
  }

  void loopFindNearKeyframes(pcl::PointCloud<PointType>::Ptr& nearKeyframes, const int& key, const int& searchNum)
  {
    // extract near keyframes
    nearKeyframes->clear();
    int cloudSize = copy_cloudKeyPoses6D->size();
    for (int i = -searchNum; i <= searchNum; ++i)
    {
      int keyNear = key + i;
      if (keyNear < 0 || keyNear >= cloudSize )
        continue;
      *nearKeyframes += *transformPointCloud(cornerCloudKeyFrames[keyNear], &copy_cloudKeyPoses6D->points[keyNear]);
      *nearKeyframes += *transformPointCloud(surfCloudKeyFrames[keyNear],   &copy_cloudKeyPoses6D->points[keyNear]);
    }

    if (nearKeyframes->empty())
      return;

    // downsample near keyframes
    pcl::PointCloud<PointType>::Ptr cloud_temp(new pcl::PointCloud<PointType>());
    downSizeFilterICP.setInputCloud(nearKeyframes);
    downSizeFilterICP.filter(*cloud_temp);
    *nearKeyframes = *cloud_temp;
  }

  void visualizeLoopClosure()
  {
    if (loopIndexContainer.empty())
      return;

    visualization_msgs::MarkerArray markerArray;
    // loop nodes
    visualization_msgs::Marker markerNode;
    markerNode.header.frame_id = odometryFrame;
    markerNode.header.stamp = timeLaserInfoStamp;
    markerNode.action = visualization_msgs::Marker::ADD;
    markerNode.type = visualization_msgs::Marker::SPHERE_LIST;
    markerNode.ns = "loop_nodes";
    markerNode.id = 0;
    markerNode.pose.orientation.w = 1;
    markerNode.scale.x = 0.3; markerNode.scale.y = 0.3; markerNode.scale.z = 0.3;
    markerNode.color.r = 0; markerNode.color.g = 0.8; markerNode.color.b = 1;
    markerNode.color.a = 1;
    // loop edges
    visualization_msgs::Marker markerEdge;
    markerEdge.header.frame_id = odometryFrame;
    markerEdge.header.stamp = timeLaserInfoStamp;
    markerEdge.action = visualization_msgs::Marker::ADD;
    markerEdge.type = visualization_msgs::Marker::LINE_LIST;
    markerEdge.ns = "loop_edges";
    markerEdge.id = 1;
    markerEdge.pose.orientation.w = 1;
    markerEdge.scale.x = 0.1;
    markerEdge.color.r = 0.9; markerEdge.color.g = 0.9; markerEdge.color.b = 0;
    markerEdge.color.a = 1;

    for (auto it = loopIndexContainer.begin(); it != loopIndexContainer.end(); ++it)
    {
      int key_cur = it->first;
      int key_pre = it->second;
      geometry_msgs::Point p;
      p.x = copy_cloudKeyPoses6D->points[key_cur].x;
      p.y = copy_cloudKeyPoses6D->points[key_cur].y;
      p.z = copy_cloudKeyPoses6D->points[key_cur].z;
      markerNode.points.push_back(p);
      markerEdge.points.push_back(p);
      p.x = copy_cloudKeyPoses6D->points[key_pre].x;
      p.y = copy_cloudKeyPoses6D->points[key_pre].y;
      p.z = copy_cloudKeyPoses6D->points[key_pre].z;
      markerNode.points.push_back(p);
      markerEdge.points.push_back(p);
    }

    markerArray.markers.push_back(markerNode);
    markerArray.markers.push_back(markerEdge);
    pubLoopConstraintEdge.publish(markerArray);
  }











  void updateInitialGuess()
  {
    // save current transformation before any processing
    incrementalOdometryAffineFront = trans2Affine3f(transformTobeMapped);

    static Eigen::Affine3f lastImuTransformation;
    // initialization
    if (cloudKeyPoses3D->points.empty())
    {
      transformTobeMapped[0] = cloudInfo.imuRollInit;
      transformTobeMapped[1] = cloudInfo.imuPitchInit;
      transformTobeMapped[2] = cloudInfo.imuYawInit;

      if (!useImuHeadingInitialization)
        transformTobeMapped[2] = 0;

      lastImuTransformation = pcl::getTransformation(0, 0, 0, cloudInfo.imuRollInit, cloudInfo.imuPitchInit, cloudInfo.imuYawInit); // save imu before return;
      return;
    }

    // use imu pre-integration estimation for pose guess
    static bool lastImuPreTransAvailable = false;
    static Eigen::Affine3f lastImuPreTransformation;
    if (cloudInfo.odomAvailable == true)
    {
      Eigen::Affine3f transBack = pcl::getTransformation(cloudInfo.initialGuessX,    cloudInfo.initialGuessY,     cloudInfo.initialGuessZ,
                                                         cloudInfo.initialGuessRoll, cloudInfo.initialGuessPitch, cloudInfo.initialGuessYaw);
      if (lastImuPreTransAvailable == false)
      {
        lastImuPreTransformation = transBack;
        lastImuPreTransAvailable = true;
      } else {
        Eigen::Affine3f transIncre = lastImuPreTransformation.inverse() * transBack;
        Eigen::Affine3f transTobe = trans2Affine3f(transformTobeMapped);
        Eigen::Affine3f transFinal = transTobe * transIncre;
        pcl::getTranslationAndEulerAngles(transFinal, transformTobeMapped[3], transformTobeMapped[4], transformTobeMapped[5],
                                          transformTobeMapped[0], transformTobeMapped[1], transformTobeMapped[2]);

        lastImuPreTransformation = transBack;

        lastImuTransformation = pcl::getTransformation(0, 0, 0, cloudInfo.imuRollInit, cloudInfo.imuPitchInit, cloudInfo.imuYawInit); // save imu before return;
        return;
      }
    }

    // use imu incremental estimation for pose guess (only rotation)
    if (cloudInfo.imuAvailable == true)
    {
      Eigen::Affine3f transBack = pcl::getTransformation(0, 0, 0, cloudInfo.imuRollInit, cloudInfo.imuPitchInit, cloudInfo.imuYawInit);
      Eigen::Affine3f transIncre = lastImuTransformation.inverse() * transBack;

      Eigen::Affine3f transTobe = trans2Affine3f(transformTobeMapped);
      Eigen::Affine3f transFinal = transTobe * transIncre;
      pcl::getTranslationAndEulerAngles(transFinal, transformTobeMapped[3], transformTobeMapped[4], transformTobeMapped[5],
                                        transformTobeMapped[0], transformTobeMapped[1], transformTobeMapped[2]);

      lastImuTransformation = pcl::getTransformation(0, 0, 0, cloudInfo.imuRollInit, cloudInfo.imuPitchInit, cloudInfo.imuYawInit); // save imu before return;
      return;
    }
  }

  void extractForLoopClosure()
  {
    pcl::PointCloud<PointType>::Ptr cloudToExtract(new pcl::PointCloud<PointType>());
    int numPoses = cloudKeyPoses3D->size();
    for (int i = numPoses-1; i >= 0; --i)
    {
      if ((int)cloudToExtract->size() <= surroundingKeyframeSize)
        cloudToExtract->push_back(cloudKeyPoses3D->points[i]);
      else
        break;
    }

    extractCloud(cloudToExtract);
  }

  void extractNearby()
  {
    pcl::PointCloud<PointType>::Ptr surroundingKeyPoses(new pcl::PointCloud<PointType>());
    pcl::PointCloud<PointType>::Ptr surroundingKeyPosesDS(new pcl::PointCloud<PointType>());
    std::vector<int> pointSearchInd;
    std::vector<float> pointSearchSqDis;

    // extract all the nearby key poses and downsample them
    kdtreeSurroundingKeyPoses->setInputCloud(cloudKeyPoses3D); // create kd-tree
    kdtreeSurroundingKeyPoses->radiusSearch(cloudKeyPoses3D->back(), (double)surroundingKeyframeSearchRadius, pointSearchInd, pointSearchSqDis);
    for (int i = 0; i < (int)pointSearchInd.size(); ++i)
    {
      int id = pointSearchInd[i];
      surroundingKeyPoses->push_back(cloudKeyPoses3D->points[id]);
    }

    downSizeFilterSurroundingKeyPoses.setInputCloud(surroundingKeyPoses);
    downSizeFilterSurroundingKeyPoses.filter(*surroundingKeyPosesDS);
    for(auto& pt : surroundingKeyPosesDS->points)
    {
      kdtreeSurroundingKeyPoses->nearestKSearch(pt, 1, pointSearchInd, pointSearchSqDis);
      pt.intensity = cloudKeyPoses3D->points[pointSearchInd[0]].intensity;
    }

    // also extract some latest key frames in case the robot rotates in one position
    int numPoses = cloudKeyPoses3D->size();
    for (int i = numPoses-1; i >= 0; --i)
    {
      if (timeLaserInfoCur - cloudKeyPoses6D->points[i].time < 10.0)
        surroundingKeyPosesDS->push_back(cloudKeyPoses3D->points[i]);
      else
        break;
    }

    extractCloud(surroundingKeyPosesDS);
  }

  void extractCloud(pcl::PointCloud<PointType>::Ptr cloudToExtract)
  {
    // fuse the map
    laserCloudCornerFromMap->clear();
    laserCloudSurfFromMap->clear();
    for (int i = 0; i < (int)cloudToExtract->size(); ++i)
    {
      if (pointDistance(cloudToExtract->points[i], cloudKeyPoses3D->back()) > surroundingKeyframeSearchRadius)
        continue;

      int thisKeyInd = (int)cloudToExtract->points[i].intensity;
      if (laserCloudMapContainer.find(thisKeyInd) != laserCloudMapContainer.end())
      {
        // transformed cloud available
        *laserCloudCornerFromMap += laserCloudMapContainer[thisKeyInd].first;
        *laserCloudSurfFromMap   += laserCloudMapContainer[thisKeyInd].second;
      } else {
        // transformed cloud not available
        pcl::PointCloud<PointType> laserCloudCornerTemp = *transformPointCloud(cornerCloudKeyFrames[thisKeyInd],  &cloudKeyPoses6D->points[thisKeyInd]);
        pcl::PointCloud<PointType> laserCloudSurfTemp = *transformPointCloud(surfCloudKeyFrames[thisKeyInd],    &cloudKeyPoses6D->points[thisKeyInd]);
        *laserCloudCornerFromMap += laserCloudCornerTemp;
        *laserCloudSurfFromMap   += laserCloudSurfTemp;
        laserCloudMapContainer[thisKeyInd] = make_pair(laserCloudCornerTemp, laserCloudSurfTemp);
      }

    }

    // Downsample the surrounding corner key frames (or map)
    downSizeFilterCorner.setInputCloud(laserCloudCornerFromMap);
    downSizeFilterCorner.filter(*laserCloudCornerFromMapDS);
    laserCloudCornerFromMapDSNum = laserCloudCornerFromMapDS->size();
    // Downsample the surrounding surf key frames (or map)
    downSizeFilterSurf.setInputCloud(laserCloudSurfFromMap);
    downSizeFilterSurf.filter(*laserCloudSurfFromMapDS);
    laserCloudSurfFromMapDSNum = laserCloudSurfFromMapDS->size();

    // clear map cache if too large
    if (laserCloudMapContainer.size() > 1000)
      laserCloudMapContainer.clear();
  }

  void extractSurroundingKeyFrames()
  {
    if (cloudKeyPoses3D->points.empty() == true)
      return;

    // if (loopClosureEnableFlag == true)
    // {
    //     extractForLoopClosure();
    // } else {
    //     extractNearby();
    // }

    extractNearby();
  }

  void downsampleCurrentScan()
  {
    // Downsample cloud from current scan
    laserCloudCornerLastDS->clear();
    downSizeFilterCorner.setInputCloud(laserCloudCornerLast);
    downSizeFilterCorner.filter(*laserCloudCornerLastDS);
    laserCloudCornerLastDSNum = laserCloudCornerLastDS->size();

    laserCloudSurfLastDS->clear();
    downSizeFilterSurf.setInputCloud(laserCloudSurfLast);
    downSizeFilterSurf.filter(*laserCloudSurfLastDS);
    laserCloudSurfLastDSNum = laserCloudSurfLastDS->size();
  }

  void updatePointAssociateToMap()
  {
    transPointAssociateToMap = trans2Affine3f(transformTobeMapped);
  }

  void cornerOptimization()
  {
    updatePointAssociateToMap();

#pragma omp parallel for num_threads(numberOfCores)
    for (int i = 0; i < laserCloudCornerLastDSNum; i++)
    {
      PointType pointOri, pointSel, coeff;
      std::vector<int> pointSearchInd;
      std::vector<float> pointSearchSqDis;

      pointOri = laserCloudCornerLastDS->points[i];
      pointAssociateToMap(&pointOri, &pointSel);
      kdtreeCornerFromMap->nearestKSearch(pointSel, 5, pointSearchInd, pointSearchSqDis);

      cv::Mat matA1(3, 3, CV_32F, cv::Scalar::all(0));
      cv::Mat matD1(1, 3, CV_32F, cv::Scalar::all(0));
      cv::Mat matV1(3, 3, CV_32F, cv::Scalar::all(0));

      if (pointSearchSqDis[4] < 1.0) {
        float cx = 0, cy = 0, cz = 0;
        for (int j = 0; j < 5; j++) {
          cx += laserCloudCornerFromMapDS->points[pointSearchInd[j]].x;
          cy += laserCloudCornerFromMapDS->points[pointSearchInd[j]].y;
          cz += laserCloudCornerFromMapDS->points[pointSearchInd[j]].z;
        }
        cx /= 5; cy /= 5;  cz /= 5;

        float a11 = 0, a12 = 0, a13 = 0, a22 = 0, a23 = 0, a33 = 0;
        for (int j = 0; j < 5; j++) {
          float ax = laserCloudCornerFromMapDS->points[pointSearchInd[j]].x - cx;
          float ay = laserCloudCornerFromMapDS->points[pointSearchInd[j]].y - cy;
          float az = laserCloudCornerFromMapDS->points[pointSearchInd[j]].z - cz;

          a11 += ax * ax; a12 += ax * ay; a13 += ax * az;
          a22 += ay * ay; a23 += ay * az;
          a33 += az * az;
        }
        a11 /= 5; a12 /= 5; a13 /= 5; a22 /= 5; a23 /= 5; a33 /= 5;

        matA1.at<float>(0, 0) = a11; matA1.at<float>(0, 1) = a12; matA1.at<float>(0, 2) = a13;
        matA1.at<float>(1, 0) = a12; matA1.at<float>(1, 1) = a22; matA1.at<float>(1, 2) = a23;
        matA1.at<float>(2, 0) = a13; matA1.at<float>(2, 1) = a23; matA1.at<float>(2, 2) = a33;

        cv::eigen(matA1, matD1, matV1);

        if (matD1.at<float>(0, 0) > 3 * matD1.at<float>(0, 1)) {

          float x0 = pointSel.x;
          float y0 = pointSel.y;
          float z0 = pointSel.z;
          float x1 = cx + 0.1 * matV1.at<float>(0, 0);
          float y1 = cy + 0.1 * matV1.at<float>(0, 1);
          float z1 = cz + 0.1 * matV1.at<float>(0, 2);
          float x2 = cx - 0.1 * matV1.at<float>(0, 0);
          float y2 = cy - 0.1 * matV1.at<float>(0, 1);
          float z2 = cz - 0.1 * matV1.at<float>(0, 2);

          float a012 = sqrt(((x0 - x1)*(y0 - y2) - (x0 - x2)*(y0 - y1)) * ((x0 - x1)*(y0 - y2) - (x0 - x2)*(y0 - y1))
                                + ((x0 - x1)*(z0 - z2) - (x0 - x2)*(z0 - z1)) * ((x0 - x1)*(z0 - z2) - (x0 - x2)*(z0 - z1))
                                + ((y0 - y1)*(z0 - z2) - (y0 - y2)*(z0 - z1)) * ((y0 - y1)*(z0 - z2) - (y0 - y2)*(z0 - z1)));

          float l12 = sqrt((x1 - x2)*(x1 - x2) + (y1 - y2)*(y1 - y2) + (z1 - z2)*(z1 - z2));

          float la = ((y1 - y2)*((x0 - x1)*(y0 - y2) - (x0 - x2)*(y0 - y1))
              + (z1 - z2)*((x0 - x1)*(z0 - z2) - (x0 - x2)*(z0 - z1))) / a012 / l12;

          float lb = -((x1 - x2)*((x0 - x1)*(y0 - y2) - (x0 - x2)*(y0 - y1))
              - (z1 - z2)*((y0 - y1)*(z0 - z2) - (y0 - y2)*(z0 - z1))) / a012 / l12;

          float lc = -((x1 - x2)*((x0 - x1)*(z0 - z2) - (x0 - x2)*(z0 - z1))
              + (y1 - y2)*((y0 - y1)*(z0 - z2) - (y0 - y2)*(z0 - z1))) / a012 / l12;

          float ld2 = a012 / l12;

          float s = 1 - 0.9 * fabs(ld2);

          coeff.x = s * la;
          coeff.y = s * lb;
          coeff.z = s * lc;
          coeff.intensity = s * ld2;

          if (s > 0.1) {
            laserCloudOriCornerVec[i] = pointOri;
            coeffSelCornerVec[i] = coeff;
            laserCloudOriCornerFlag[i] = true;
          }
        }
      }
    }
  }

  void surfOptimization()
  {
    updatePointAssociateToMap();

#pragma omp parallel for num_threads(numberOfCores)
    for (int i = 0; i < laserCloudSurfLastDSNum; i++)
    {
      PointType pointOri, pointSel, coeff;
      std::vector<int> pointSearchInd;
      std::vector<float> pointSearchSqDis;

      pointOri = laserCloudSurfLastDS->points[i];
      pointAssociateToMap(&pointOri, &pointSel);
      kdtreeSurfFromMap->nearestKSearch(pointSel, 5, pointSearchInd, pointSearchSqDis);

      Eigen::Matrix<float, 5, 3> matA0;
      Eigen::Matrix<float, 5, 1> matB0;
      Eigen::Vector3f matX0;

      matA0.setZero();
      matB0.fill(-1);
      matX0.setZero();

      if (pointSearchSqDis[4] < 1.0) {
        for (int j = 0; j < 5; j++) {
          matA0(j, 0) = laserCloudSurfFromMapDS->points[pointSearchInd[j]].x;
          matA0(j, 1) = laserCloudSurfFromMapDS->points[pointSearchInd[j]].y;
          matA0(j, 2) = laserCloudSurfFromMapDS->points[pointSearchInd[j]].z;
        }

        matX0 = matA0.colPivHouseholderQr().solve(matB0);

        float pa = matX0(0, 0);
        float pb = matX0(1, 0);
        float pc = matX0(2, 0);
        float pd = 1;

        float ps = sqrt(pa * pa + pb * pb + pc * pc);
        pa /= ps; pb /= ps; pc /= ps; pd /= ps;

        bool planeValid = true;
        for (int j = 0; j < 5; j++) {
          if (fabs(pa * laserCloudSurfFromMapDS->points[pointSearchInd[j]].x +
              pb * laserCloudSurfFromMapDS->points[pointSearchInd[j]].y +
              pc * laserCloudSurfFromMapDS->points[pointSearchInd[j]].z + pd) > 0.2) {
            planeValid = false;
            break;
          }
        }

        if (planeValid) {
          float pd2 = pa * pointSel.x + pb * pointSel.y + pc * pointSel.z + pd;

          float s = 1 - 0.9 * fabs(pd2) / sqrt(sqrt(pointOri.x * pointOri.x
                                                        + pointOri.y * pointOri.y + pointOri.z * pointOri.z));

          coeff.x = s * pa;
          coeff.y = s * pb;
          coeff.z = s * pc;
          coeff.intensity = s * pd2;

          if (s > 0.1) {
            laserCloudOriSurfVec[i] = pointOri;
            coeffSelSurfVec[i] = coeff;
            laserCloudOriSurfFlag[i] = true;
          }
        }
      }
    }
  }

  void combineOptimizationCoeffs()
  {
    // combine corner coeffs
    for (int i = 0; i < laserCloudCornerLastDSNum; ++i){
      if (laserCloudOriCornerFlag[i] == true){
        laserCloudOri->push_back(laserCloudOriCornerVec[i]);
        coeffSel->push_back(coeffSelCornerVec[i]);
      }
    }
    // combine surf coeffs
    for (int i = 0; i < laserCloudSurfLastDSNum; ++i){
      if (laserCloudOriSurfFlag[i] == true){
        laserCloudOri->push_back(laserCloudOriSurfVec[i]);
        coeffSel->push_back(coeffSelSurfVec[i]);
      }
    }
    // reset flag for next iteration
    std::fill(laserCloudOriCornerFlag.begin(), laserCloudOriCornerFlag.end(), false);
    std::fill(laserCloudOriSurfFlag.begin(), laserCloudOriSurfFlag.end(), false);
  }

  bool LMOptimization(int iterCount)
  {
    // This optimization is from the original loam_velodyne by Ji Zhang, need to cope with coordinate transformation
    // lidar <- camera      ---     camera <- lidar
    // x = z                ---     x = y
    // y = x                ---     y = z
    // z = y                ---     z = x
    // roll = yaw           ---     roll = pitch
    // pitch = roll         ---     pitch = yaw
    // yaw = pitch          ---     yaw = roll

    // lidar -> camera
    float srx = sin(transformTobeMapped[1]);
    float crx = cos(transformTobeMapped[1]);
    float sry = sin(transformTobeMapped[2]);
    float cry = cos(transformTobeMapped[2]);
    float srz = sin(transformTobeMapped[0]);
    float crz = cos(transformTobeMapped[0]);

    int laserCloudSelNum = laserCloudOri->size();
    if (laserCloudSelNum < 50) {
      return false;
    }

    cv::Mat matA(laserCloudSelNum, 6, CV_32F, cv::Scalar::all(0));
    cv::Mat matAt(6, laserCloudSelNum, CV_32F, cv::Scalar::all(0));
    cv::Mat matAtA(6, 6, CV_32F, cv::Scalar::all(0));
    cv::Mat matB(laserCloudSelNum, 1, CV_32F, cv::Scalar::all(0));
    cv::Mat matAtB(6, 1, CV_32F, cv::Scalar::all(0));
    cv::Mat matX(6, 1, CV_32F, cv::Scalar::all(0));

    PointType pointOri, coeff;

    for (int i = 0; i < laserCloudSelNum; i++) {
      // lidar -> camera
      pointOri.x = laserCloudOri->points[i].y;
      pointOri.y = laserCloudOri->points[i].z;
      pointOri.z = laserCloudOri->points[i].x;
      // lidar -> camera
      coeff.x = coeffSel->points[i].y;
      coeff.y = coeffSel->points[i].z;
      coeff.z = coeffSel->points[i].x;
      coeff.intensity = coeffSel->points[i].intensity;
      // in camera
      float arx = (crx*sry*srz*pointOri.x + crx*crz*sry*pointOri.y - srx*sry*pointOri.z) * coeff.x
          + (-srx*srz*pointOri.x - crz*srx*pointOri.y - crx*pointOri.z) * coeff.y
          + (crx*cry*srz*pointOri.x + crx*cry*crz*pointOri.y - cry*srx*pointOri.z) * coeff.z;

      float ary = ((cry*srx*srz - crz*sry)*pointOri.x
          + (sry*srz + cry*crz*srx)*pointOri.y + crx*cry*pointOri.z) * coeff.x
          + ((-cry*crz - srx*sry*srz)*pointOri.x
              + (cry*srz - crz*srx*sry)*pointOri.y - crx*sry*pointOri.z) * coeff.z;

      float arz = ((crz*srx*sry - cry*srz)*pointOri.x + (-cry*crz-srx*sry*srz)*pointOri.y)*coeff.x
          + (crx*crz*pointOri.x - crx*srz*pointOri.y) * coeff.y
          + ((sry*srz + cry*crz*srx)*pointOri.x + (crz*sry-cry*srx*srz)*pointOri.y)*coeff.z;
      // camera -> lidar
      matA.at<float>(i, 0) = arz;
      matA.at<float>(i, 1) = arx;
      matA.at<float>(i, 2) = ary;
      matA.at<float>(i, 3) = coeff.z;
      matA.at<float>(i, 4) = coeff.x;
      matA.at<float>(i, 5) = coeff.y;
      matB.at<float>(i, 0) = -coeff.intensity;
    }

    cv::transpose(matA, matAt);
    matAtA = matAt * matA;
    matAtB = matAt * matB;
    cv::solve(matAtA, matAtB, matX, cv::DECOMP_QR);

    if (iterCount == 0) {

      cv::Mat matE(1, 6, CV_32F, cv::Scalar::all(0));
      cv::Mat matV(6, 6, CV_32F, cv::Scalar::all(0));
      cv::Mat matV2(6, 6, CV_32F, cv::Scalar::all(0));

      cv::eigen(matAtA, matE, matV);
      matV.copyTo(matV2);

      isDegenerate = false;
      float eignThre[6] = {100, 100, 100, 100, 100, 100};
      for (int i = 5; i >= 0; i--) {
        if (matE.at<float>(0, i) < eignThre[i]) {
          for (int j = 0; j < 6; j++) {
            matV2.at<float>(i, j) = 0;
          }
          isDegenerate = true;
        } else {
          break;
        }
      }
      matP = matV.inv() * matV2;
    }

    if (isDegenerate)
    {
      cv::Mat matX2(6, 1, CV_32F, cv::Scalar::all(0));
      matX.copyTo(matX2);
      matX = matP * matX2;
    }

    transformTobeMapped[0] += matX.at<float>(0, 0);
    transformTobeMapped[1] += matX.at<float>(1, 0);
    transformTobeMapped[2] += matX.at<float>(2, 0);
    transformTobeMapped[3] += matX.at<float>(3, 0);
    transformTobeMapped[4] += matX.at<float>(4, 0);
    transformTobeMapped[5] += matX.at<float>(5, 0);

    float deltaR = sqrt(
        pow(pcl::rad2deg(matX.at<float>(0, 0)), 2) +
            pow(pcl::rad2deg(matX.at<float>(1, 0)), 2) +
            pow(pcl::rad2deg(matX.at<float>(2, 0)), 2));
    float deltaT = sqrt(
        pow(matX.at<float>(3, 0) * 100, 2) +
            pow(matX.at<float>(4, 0) * 100, 2) +
            pow(matX.at<float>(5, 0) * 100, 2));

    if (deltaR < 0.05 && deltaT < 0.05) {
      return true; // converged
    }
    return false; // keep optimizing
  }

  void scan2MapOptimization()
  {
    if (cloudKeyPoses3D->points.empty())
      return;

    if (laserCloudCornerLastDSNum > edgeFeatureMinValidNum && laserCloudSurfLastDSNum > surfFeatureMinValidNum)
    {
      kdtreeCornerFromMap->setInputCloud(laserCloudCornerFromMapDS);
      kdtreeSurfFromMap->setInputCloud(laserCloudSurfFromMapDS);

      for (int iterCount = 0; iterCount < 30; iterCount++)
      {
        laserCloudOri->clear();
        coeffSel->clear();

        cornerOptimization();
        surfOptimization();

        combineOptimizationCoeffs();

        if (LMOptimization(iterCount) == true)
          break;
      }

      transformUpdate();
    } else {
      ROS_WARN("Not enough features! Only %d edge and %d planar features available.", laserCloudCornerLastDSNum, laserCloudSurfLastDSNum);
    }
  }

  void transformUpdate()
  {
    if (cloudInfo.imuAvailable == true)
    {
      if (std::abs(cloudInfo.imuPitchInit) < 1.4)
      {
        double imuWeight = imuRPYWeight;
        tf::Quaternion imuQuaternion;
        tf::Quaternion transformQuaternion;
        double rollMid, pitchMid, yawMid;

        // slerp roll
        transformQuaternion.setRPY(transformTobeMapped[0], 0, 0);
        imuQuaternion.setRPY(cloudInfo.imuRollInit, 0, 0);
        tf::Matrix3x3(transformQuaternion.slerp(imuQuaternion, imuWeight)).getRPY(rollMid, pitchMid, yawMid);
        transformTobeMapped[0] = rollMid;

        // slerp pitch
        transformQuaternion.setRPY(0, transformTobeMapped[1], 0);
        imuQuaternion.setRPY(0, cloudInfo.imuPitchInit, 0);
        tf::Matrix3x3(transformQuaternion.slerp(imuQuaternion, imuWeight)).getRPY(rollMid, pitchMid, yawMid);
        transformTobeMapped[1] = pitchMid;
      }
    }

    transformTobeMapped[0] = constraintTransformation(transformTobeMapped[0], rotation_tollerance);
    transformTobeMapped[1] = constraintTransformation(transformTobeMapped[1], rotation_tollerance);
    transformTobeMapped[5] = constraintTransformation(transformTobeMapped[5], z_tollerance);

    incrementalOdometryAffineBack = trans2Affine3f(transformTobeMapped);
  }

  float constraintTransformation(float value, float limit)
  {
    if (value < -limit)
      value = -limit;
    if (value > limit)
      value = limit;

    return value;
  }

  bool saveFrame()
  {
    if (cloudKeyPoses3D->points.empty())
      return true;

    if (sensor == SensorType::LIVOX)
    {
      if (timeLaserInfoCur - cloudKeyPoses6D->back().time > 1.0)
        return true;
    }

    Eigen::Affine3f transStart = pclPointToAffine3f(cloudKeyPoses6D->back());
    Eigen::Affine3f transFinal = pcl::getTransformation(transformTobeMapped[3], transformTobeMapped[4], transformTobeMapped[5],
                                                        transformTobeMapped[0], transformTobeMapped[1], transformTobeMapped[2]);
    Eigen::Affine3f transBetween = transStart.inverse() * transFinal;
    float x, y, z, roll, pitch, yaw;
    pcl::getTranslationAndEulerAngles(transBetween, x, y, z, roll, pitch, yaw);

    if (abs(roll)  < surroundingkeyframeAddingAngleThreshold &&
        abs(pitch) < surroundingkeyframeAddingAngleThreshold &&
        abs(yaw)   < surroundingkeyframeAddingAngleThreshold &&
        sqrt(x*x + y*y + z*z) < surroundingkeyframeAddingDistThreshold)
      return false;

    return true;
  }

  void addOdomFactor()
  {
    if (cloudKeyPoses3D->points.empty())
    {
      noiseModel::Diagonal::shared_ptr priorNoise = noiseModel::Diagonal::Variances((Vector(6) << 1e-2, 1e-2, M_PI*M_PI, 1e8, 1e8, 1e8).finished()); // rad*rad, meter*meter
      gtSAMgraph.add(PriorFactor<Pose3>(0, trans2gtsamPose(transformTobeMapped), priorNoise));
      initialEstimate.insert(0, trans2gtsamPose(transformTobeMapped));
    }else{
      noiseModel::Diagonal::shared_ptr odometryNoise = noiseModel::Diagonal::Variances((Vector(6) << 1e-6, 1e-6, 1e-6, 1e-4, 1e-4, 1e-4).finished());
      gtsam::Pose3 poseFrom = pclPointTogtsamPose3(cloudKeyPoses6D->points.back());
      gtsam::Pose3 poseTo   = trans2gtsamPose(transformTobeMapped);
      gtSAMgraph.add(BetweenFactor<Pose3>(cloudKeyPoses3D->size()-1, cloudKeyPoses3D->size(), poseFrom.between(poseTo), odometryNoise));
      initialEstimate.insert(cloudKeyPoses3D->size(), poseTo);
    }
  }

  void addGPSFactor()
  {
    if (gpsQueue.empty())
      return;

    // wait for system initialized and settles down
    if (cloudKeyPoses3D->points.empty())
      return;
    else
    {
      if (pointDistance(cloudKeyPoses3D->front(), cloudKeyPoses3D->back()) < 5.0)
        return;
    }

    // pose covariance small, no need to correct
    if (poseCovariance(3,3) < poseCovThreshold && poseCovariance(4,4) < poseCovThreshold)
      return;

    // last gps position
    static PointType lastGPSPoint;

    while (!gpsQueue.empty())
    {
      if (gpsQueue.front().header.stamp.toSec() < timeLaserInfoCur - 0.2)
      {
        // message too old
        gpsQueue.pop_front();
      }
      else if (gpsQueue.front().header.stamp.toSec() > timeLaserInfoCur + 0.2)
      {
        // message too new
        break;
      }
      else
      {
        nav_msgs::Odometry thisGPS = gpsQueue.front();
        gpsQueue.pop_front();

        // GPS too noisy, skip
        float noise_x = thisGPS.pose.covariance[0];
        float noise_y = thisGPS.pose.covariance[7];
        float noise_z = thisGPS.pose.covariance[14];
        if (noise_x > gpsCovThreshold || noise_y > gpsCovThreshold)
          continue;

        float gps_x = thisGPS.pose.pose.position.x;
        float gps_y = thisGPS.pose.pose.position.y;
        float gps_z = thisGPS.pose.pose.position.z;
        if (!useGpsElevation)
        {
          gps_z = transformTobeMapped[5];
          noise_z = 0.01;
        }

        // GPS not properly initialized (0,0,0)
        if (abs(gps_x) < 1e-6 && abs(gps_y) < 1e-6)
          continue;

        // Add GPS every a few meters
        PointType curGPSPoint;
        curGPSPoint.x = gps_x;
        curGPSPoint.y = gps_y;
        curGPSPoint.z = gps_z;
        if (pointDistance(curGPSPoint, lastGPSPoint) < 5.0)
          continue;
        else
          lastGPSPoint = curGPSPoint;

        gtsam::Vector Vector3(3);
        Vector3 << max(noise_x, 1.0f), max(noise_y, 1.0f), max(noise_z, 1.0f);
        noiseModel::Diagonal::shared_ptr gps_noise = noiseModel::Diagonal::Variances(Vector3);
        gtsam::GPSFactor gps_factor(cloudKeyPoses3D->size(), gtsam::Point3(gps_x, gps_y, gps_z), gps_noise);
        gtSAMgraph.add(gps_factor);

        aLoopIsClosed = true;
        break;
      }
    }
  }

  void addLoopFactor()
  {
    if (loopIndexQueue.empty())
      return;

    for (int i = 0; i < (int)loopIndexQueue.size(); ++i)
    {
      int indexFrom = loopIndexQueue[i].first;
      int indexTo = loopIndexQueue[i].second;
      gtsam::Pose3 poseBetween = loopPoseQueue[i];
      gtsam::noiseModel::Diagonal::shared_ptr noiseBetween = loopNoiseQueue[i];
      gtSAMgraph.add(BetweenFactor<Pose3>(indexFrom, indexTo, poseBetween, noiseBetween));
    }

    loopIndexQueue.clear();
    loopPoseQueue.clear();
    loopNoiseQueue.clear();
    aLoopIsClosed = true;
  }

  void saveKeyFramesAndFactor()
  {
    if (saveFrame() == false)
      return;

    // odom factor
    addOdomFactor();

    // gps factor
    addGPSFactor();

    // loop factor
    addLoopFactor();

    // cout << "****************************************************" << endl;
    // gtSAMgraph.print("GTSAM Graph:\n");

    // update iSAM
    isam->update(gtSAMgraph, initialEstimate);
    isam->update();

    if (aLoopIsClosed == true)
    {
      isam->update();
      isam->update();
      isam->update();
      isam->update();
      isam->update();
    }

    gtSAMgraph.resize(0);
    initialEstimate.clear();

    //save key poses
    PointType thisPose3D;
    PointTypePose thisPose6D;
    Pose3 latestEstimate;

    isamCurrentEstimate = isam->calculateEstimate();
    latestEstimate = isamCurrentEstimate.at<Pose3>(isamCurrentEstimate.size()-1);
    // cout << "****************************************************" << endl;
    // isamCurrentEstimate.print("Current estimate: ");

    thisPose3D.x = latestEstimate.translation().x();
    thisPose3D.y = latestEstimate.translation().y();
    thisPose3D.z = latestEstimate.translation().z();
    thisPose3D.intensity = cloudKeyPoses3D->size(); // this can be used as index
    cloudKeyPoses3D->push_back(thisPose3D);

    thisPose6D.x = thisPose3D.x;
    thisPose6D.y = thisPose3D.y;
    thisPose6D.z = thisPose3D.z;
    thisPose6D.intensity = thisPose3D.intensity ; // this can be used as index
    thisPose6D.roll  = latestEstimate.rotation().roll();
    thisPose6D.pitch = latestEstimate.rotation().pitch();
    thisPose6D.yaw   = latestEstimate.rotation().yaw();
    thisPose6D.time = timeLaserInfoCur;
    cloudKeyPoses6D->push_back(thisPose6D);

    // cout << "****************************************************" << endl;
    // cout << "Pose covariance:" << endl;
    // cout << isam->marginalCovariance(isamCurrentEstimate.size()-1) << endl << endl;
    poseCovariance = isam->marginalCovariance(isamCurrentEstimate.size()-1);

    // save updated transform
    transformTobeMapped[0] = latestEstimate.rotation().roll();
    transformTobeMapped[1] = latestEstimate.rotation().pitch();
    transformTobeMapped[2] = latestEstimate.rotation().yaw();
    transformTobeMapped[3] = latestEstimate.translation().x();
    transformTobeMapped[4] = latestEstimate.translation().y();
    transformTobeMapped[5] = latestEstimate.translation().z();

    // save all the received edge and surf points
    pcl::PointCloud<PointType>::Ptr thisCornerKeyFrame(new pcl::PointCloud<PointType>());
    pcl::PointCloud<PointType>::Ptr thisSurfKeyFrame(new pcl::PointCloud<PointType>());
    pcl::copyPointCloud(*laserCloudCornerLastDS,  *thisCornerKeyFrame);
    pcl::copyPointCloud(*laserCloudSurfLastDS,    *thisSurfKeyFrame);

    // save key frame cloud
    cornerCloudKeyFrames.push_back(thisCornerKeyFrame);
    surfCloudKeyFrames.push_back(thisSurfKeyFrame);

    // save path for visualization
    updatePath(thisPose6D);
  }

  void correctPoses()
  {
    if (cloudKeyPoses3D->points.empty())
      return;

    if (aLoopIsClosed == true)
    {
      // clear map cache
      laserCloudMapContainer.clear();
      // clear path
      globalPath.poses.clear();
      // update key poses
      int numPoses = isamCurrentEstimate.size();
      for (int i = 0; i < numPoses; ++i)
      {
        cloudKeyPoses3D->points[i].x = isamCurrentEstimate.at<Pose3>(i).translation().x();
        cloudKeyPoses3D->points[i].y = isamCurrentEstimate.at<Pose3>(i).translation().y();
        cloudKeyPoses3D->points[i].z = isamCurrentEstimate.at<Pose3>(i).translation().z();

        cloudKeyPoses6D->points[i].x = cloudKeyPoses3D->points[i].x;
        cloudKeyPoses6D->points[i].y = cloudKeyPoses3D->points[i].y;
        cloudKeyPoses6D->points[i].z = cloudKeyPoses3D->points[i].z;
        cloudKeyPoses6D->points[i].roll  = isamCurrentEstimate.at<Pose3>(i).rotation().roll();
        cloudKeyPoses6D->points[i].pitch = isamCurrentEstimate.at<Pose3>(i).rotation().pitch();
        cloudKeyPoses6D->points[i].yaw   = isamCurrentEstimate.at<Pose3>(i).rotation().yaw();

        updatePath(cloudKeyPoses6D->points[i]);
      }

      aLoopIsClosed = false;
    }
  }

  void updatePath(const PointTypePose& pose_in)
  {
    geometry_msgs::PoseStamped pose_stamped;
    pose_stamped.header.stamp = ros::Time().fromSec(pose_in.time);
    pose_stamped.header.frame_id = odometryFrame;
    pose_stamped.pose.position.x = pose_in.x;
    pose_stamped.pose.position.y = pose_in.y;
    pose_stamped.pose.position.z = pose_in.z;
    tf::Quaternion q = tf::createQuaternionFromRPY(pose_in.roll, pose_in.pitch, pose_in.yaw);
    pose_stamped.pose.orientation.x = q.x();
    pose_stamped.pose.orientation.y = q.y();
    pose_stamped.pose.orientation.z = q.z();
    pose_stamped.pose.orientation.w = q.w();

    globalPath.poses.push_back(pose_stamped);
  }

  void publishOdometry()
  {
    // Publish odometry for ROS (global)
    nav_msgs::Odometry laserOdometryROS;
    laserOdometryROS.header.stamp = timeLaserInfoStamp;
    laserOdometryROS.header.frame_id = odometryFrame;
    laserOdometryROS.child_frame_id = "odom_mapping";
    laserOdometryROS.pose.pose.position.x = transformTobeMapped[3];
    laserOdometryROS.pose.pose.position.y = transformTobeMapped[4];
    laserOdometryROS.pose.pose.position.z = transformTobeMapped[5];
    laserOdometryROS.pose.pose.orientation = tf::createQuaternionMsgFromRollPitchYaw(transformTobeMapped[0], transformTobeMapped[1], transformTobeMapped[2]);
    pubLaserOdometryGlobal.publish(laserOdometryROS);

    // Publish TF
    static tf::TransformBroadcaster br;
    tf::Transform t_odom_to_lidar = tf::Transform(tf::createQuaternionFromRPY(transformTobeMapped[0], transformTobeMapped[1], transformTobeMapped[2]),
                                                  tf::Vector3(transformTobeMapped[3], transformTobeMapped[4], transformTobeMapped[5]));
    tf::StampedTransform trans_odom_to_lidar = tf::StampedTransform(t_odom_to_lidar, timeLaserInfoStamp, odometryFrame, "lidar_link");
    br.sendTransform(trans_odom_to_lidar);

    // Publish odometry for ROS (incremental)
    static bool lastIncreOdomPubFlag = false;
    static nav_msgs::Odometry laserOdomIncremental; // incremental odometry msg
    static Eigen::Affine3f increOdomAffine; // incremental odometry in affine
    if (lastIncreOdomPubFlag == false)
    {
      lastIncreOdomPubFlag = true;
      laserOdomIncremental = laserOdometryROS;
      increOdomAffine = trans2Affine3f(transformTobeMapped);
    } else {
      Eigen::Affine3f affineIncre = incrementalOdometryAffineFront.inverse() * incrementalOdometryAffineBack;
      increOdomAffine = increOdomAffine * affineIncre;
      float x, y, z, roll, pitch, yaw;
      pcl::getTranslationAndEulerAngles (increOdomAffine, x, y, z, roll, pitch, yaw);
      if (cloudInfo.imuAvailable == true)
      {
        if (std::abs(cloudInfo.imuPitchInit) < 1.4)
        {
          double imuWeight = 0.1;
          tf::Quaternion imuQuaternion;
          tf::Quaternion transformQuaternion;
          double rollMid, pitchMid, yawMid;

          // slerp roll
          transformQuaternion.setRPY(roll, 0, 0);
          imuQuaternion.setRPY(cloudInfo.imuRollInit, 0, 0);
          tf::Matrix3x3(transformQuaternion.slerp(imuQuaternion, imuWeight)).getRPY(rollMid, pitchMid, yawMid);
          roll = rollMid;

          // slerp pitch
          transformQuaternion.setRPY(0, pitch, 0);
          imuQuaternion.setRPY(0, cloudInfo.imuPitchInit, 0);
          tf::Matrix3x3(transformQuaternion.slerp(imuQuaternion, imuWeight)).getRPY(rollMid, pitchMid, yawMid);
          pitch = pitchMid;
        }
      }
      laserOdomIncremental.header.stamp = timeLaserInfoStamp;
      laserOdomIncremental.header.frame_id = odometryFrame;
      laserOdomIncremental.child_frame_id = "odom_mapping";
      laserOdomIncremental.pose.pose.position.x = x;
      laserOdomIncremental.pose.pose.position.y = y;
      laserOdomIncremental.pose.pose.position.z = z;
      laserOdomIncremental.pose.pose.orientation = tf::createQuaternionMsgFromRollPitchYaw(roll, pitch, yaw);
      if (isDegenerate)
        laserOdomIncremental.pose.covariance[0] = 1;
      else
        laserOdomIncremental.pose.covariance[0] = 0;
    }
    pubLaserOdometryIncremental.publish(laserOdomIncremental);
  }

  void publishFrames()
  {
    if (cloudKeyPoses3D->points.empty())
      return;
    // publish key poses
    publishCloud(pubKeyPoses, cloudKeyPoses3D, timeLaserInfoStamp, odometryFrame);
    // Publish surrounding key frames
    publishCloud(pubRecentKeyFrames, laserCloudSurfFromMapDS, timeLaserInfoStamp, odometryFrame);
    // publish registered key frame
    if (pubRecentKeyFrame.getNumSubscribers() != 0)
    {
      pcl::PointCloud<PointType>::Ptr cloudOut(new pcl::PointCloud<PointType>());
      PointTypePose thisPose6D = trans2PointTypePose(transformTobeMapped);
      *cloudOut += *transformPointCloud(laserCloudCornerLastDS,  &thisPose6D);
      *cloudOut += *transformPointCloud(laserCloudSurfLastDS,    &thisPose6D);
      publishCloud(pubRecentKeyFrame, cloudOut, timeLaserInfoStamp, odometryFrame);
    }
    // publish registered high-res raw cloud
    if (pubCloudRegisteredRaw.getNumSubscribers() != 0)
    {
      pcl::PointCloud<PointType>::Ptr cloudOut(new pcl::PointCloud<PointType>());
      pcl::fromROSMsg(cloudInfo.cloud_deskewed, *cloudOut);
      PointTypePose thisPose6D = trans2PointTypePose(transformTobeMapped);
      *cloudOut = *transformPointCloud(cloudOut,  &thisPose6D);
      publishCloud(pubCloudRegisteredRaw, cloudOut, timeLaserInfoStamp, odometryFrame);
    }
    // publish path
    if (pubPath.getNumSubscribers() != 0)
    {
      globalPath.header.stamp = timeLaserInfoStamp;
      globalPath.header.frame_id = odometryFrame;
      pubPath.publish(globalPath);
    }
    // publish SLAM infomation for 3rd-party usage
    static int lastSLAMInfoPubSize = -1;
    if (pubSLAMInfo.getNumSubscribers() != 0)
    {
      if (lastSLAMInfoPubSize != cloudKeyPoses6D->size())
      {
        lio_sam_6axis::cloud_info slamInfo;
        slamInfo.header.stamp = timeLaserInfoStamp;
        pcl::PointCloud<PointType>::Ptr cloudOut(new pcl::PointCloud<PointType>());
        *cloudOut += *laserCloudCornerLastDS;
        *cloudOut += *laserCloudSurfLastDS;
        slamInfo.key_frame_cloud = publishCloud(ros::Publisher(), cloudOut, timeLaserInfoStamp, lidarFrame);
        slamInfo.key_frame_poses = publishCloud(ros::Publisher(), cloudKeyPoses6D, timeLaserInfoStamp, odometryFrame);
        pcl::PointCloud<PointType>::Ptr localMapOut(new pcl::PointCloud<PointType>());
        *localMapOut += *laserCloudCornerFromMapDS;
        *localMapOut += *laserCloudSurfFromMapDS;
        slamInfo.key_frame_map = publishCloud(ros::Publisher(), localMapOut, timeLaserInfoStamp, odometryFrame);
        pubSLAMInfo.publish(slamInfo);
        lastSLAMInfoPubSize = cloudKeyPoses6D->size();
      }
    }
  }
};


int main(int argc, char** argv)
{
  ros::init(argc, argv, "lio_sam_6axis");

  mapOptimization MO;

  ROS_INFO("\033[1;32m----> Map Optimization Started.\033[0m");

  std::thread loopthread(&mapOptimization::loopClosureThread, &MO);
  std::thread visualizeMapThread(&mapOptimization::visualizeGlobalMapThread, &MO);

  ros::spin();

  loopthread.join();
  visualizeMapThread.join();

  return 0;
}